Method for predicting rate of progression of parkinson's disease based on molecular genetic data

Abstract

FIELD: neurology.SUBSTANCE: used to predict the rate of progression of Parkinson's disease. The genotypes of the rs12411216 polymorphism of the GBA gene and the rs6265 polymorphism of the BDNF gene are determined. The obtained data are coded and substituted into the formula for calculating the probability of the rate of progression (P). A P value of 0.199 or greater predicts rapid progression of Parkinson's disease. A P value of less than 0.199 predicts a slow rate of progression of Parkinson's disease.EFFECT: method provides the ability to predict the rate of progression of Parkinson's disease in the early stages of the disease by constructing a logistic regression model based on molecular genetic data.1 cl, 1 tbl, 2 ex

Description

[0001] The invention relates to medicine, specifically neurology, and can be used to predict the course of Parkinson's disease (PD), specifically the rate of progression in patients with an already-onset neurodegenerative process. The method enables the prediction of the disease's progression and the development of appropriate correction methods using so-called modifiable factors, which can clinically "slow down" the functional impairment of various neurotransmitter systems in the brain responsible for regulating the rate of progression.

[0002] Currently, the assessment and development of PD are fairly well understood, and efforts are being made to provide comprehensive, scientifically validated methods for their development, as well as effective diagnostic methods for these methods. However, the implementation of these approaches has not yet fully utilized the potential of modern information technology, innovative neuroimaging tools, and molecular genetic features that improve the effectiveness of diagnostics at the earliest stages and deserve the close attention of medical professionals.

[0003] A known method for identifying genetic markers of late-onset PD [1] is based on exome sequencing of 11 genes in patients with familial or juvenile forms of PD, with a preliminary analysis of known mutations and polymorphic variants in the LRRK2 and PARK2 genes using the multiplex ligase polymerase reaction (MLPR). Patients are selected for exome sequencing, excluding those patients in whose DNA known markers have been identified. The main markers associated with the development of the late form of PD are identified. The invention accelerates and reduces the cost of mutation analysis in patients with PD by introducing a preliminary step of typing common mutations using the MLPR method before the stage of whole-exome DNA sequencing.

[0004] The invention has the disadvantage that it is not intended to predict the course of a neurodegenerative disease.

[0005] A method for diagnosing neurodegenerative processes in Parkinson's disease using functional MRI (fMRI) is known. The invention relates to medicine, neurology, and the assessment of cognitive processes and visuospatial perception in the brain of patients with Parkinson's disease (PD). It can be used as a biomarker of the ongoing neurodegenerative process and to evaluate the effectiveness of treatment. The brain is examined using fMRI at rest, identifying areas of neural activity in the default mode network (DMN). These areas are represented by areas of the precuneus, posterior cingulate gyri, medial frontal lobes, and inferior parietal lobes of the right and left cerebral hemispheres.In the presence of a statistically significant decrease in spontaneous neuronal activity only in the inferior parietal lobule of the right hemisphere of the DPRN relative to the level of neuronal activity of the DPRN in the rest of its zones, initial neurodegenerative manifestations in PD are diagnosed. The method ensures high accuracy in diagnosing the neurodegenerative process in PD at an early stage of its manifestation (method for diagnosing the neurodegenerative process in Parkinson's disease [2].

[0006] A disadvantage is the lack of standardization of presets during the study, which increases the time required. Furthermore, this method can only be used to clarify the diagnosis and does not reliably predict the rate of disease progression, which is crucial for determining the quality of life of patients with PD and choosing a treatment method.

[0007] This imposes a number of limitations in the application of this technique due to its unavailability in real clinical practice for assessing the rate of disease progression and requires the development of new technical and methodological approaches.

[0008] The closest to the claimed technical solution in terms of technical essence and achievable technical result is a method for diagnosing PD associated with mutations in the glucocerebrosidase gene [3]. It is intended for the diagnosis of PD associated with mutations in the glucocerebrosidase (GBA) gene. The concentration of the lysosphingolipid hexosylsphingosine (HexSph), which is a mixture of the lysosphingolipids glucosylsphingosine (GlcSph) and galactosylsphingosine (GalSph), is measured in the blood. The HexSph concentration threshold is determined in a primary culture of blood macrophages obtained from human blood monocytes, which are applied to filter cards at a concentration of 2*106 cells / ml. At HexSph concentrations greater than 32.15 ng / ml, PD is diagnosed in heterozygous carriers of the GBA gene mutation. The invention provides a marker for diagnosing the onset of PD associated with GBA gene mutations in a group of heterozygous carriers of GBA gene mutations.

[0009] However, this technique has a number of disadvantages, in particular, it provides the creation of a marker for the diagnosis of the onset of PD associated with mutations in the GBA gene in a group of heterozygous carriers of mutations in the GBA gene, but is not intended to predict the rate of progression of neurodegenerative disease.

[0010] The present invention is based on the task of developing a method for predicting the rate of progression of PD based on molecular genetic data.

[0011] The technical result is achieved through molecular genetic research, assessing the rate of progression of motor and non-motor disorders, which will subsequently facilitate early correction of PD symptoms in order to improve the quality of life of patients and their relatives.

[0012] Thus, the technical result of the claimed method is to predict the rate of progression of PD, at the early stages of the disease using a safe and inexpensive method - molecular genetic testing.

[0013] Specific molecular genetic data are used as predictors in patients with a clinically confirmed diagnosis of PD to determine the rate of progression of motor and non-motor symptoms.

[0014] To predict the rate of PD progression, a model was constructed based on molecular genetic data. The following characteristics served as predictors:

[0015] 1. genotype AA of polymorphism rs12411216 of the GBA gene;

[0016] 2. genotype AA of rs6265 polymorphism of the BDNF gene;

[0017] 3. genotype AA of polymorphism rs591323 of the FGF20 gene;

[0018] 4. allele C of the rs80306347 polymorphism of the LRP1B gene;

[0019] 5. allele T of polymorphism rs11711441 of the LAMP3 / MCCC1 gene;

[0020] 6. allele G of polymorphism rs55861089 of the CTSD gene;

[0021] 7. allele G of polymorphism rs17565841 of the OCA2 gene;

[0022] 8. T allele of the rs2107538 polymorphism of the RANTES gene.

[0023] The modeling was performed using the backward stepwise Wald method of sequentially eliminating variables from the model. A statistically significant model was obtained (Chi-square=94.0 p<0.001), the quality of the model was less than satisfactory (R coefficient). 2 Nigelkerka is 0.48).

[0024] During the stepwise selection of predictors, the following characteristics were excluded as insignificant: AA genotype of the rs591323 polymorphism of the FGF20 gene (p=0.13); C allele of the rs80306347 polymorphism of the LRP1B gene (p=0.50); ​​T allele of the rs11711441 polymorphism of the LAMP3 / MCCC1 gene (p=0.94); G allele of the rs55861089 polymorphism of the CTSD gene (p=0.7926); G allele of the rs17565841 polymorphism of the OCA2 gene (p=0.65); T allele of the rs2107538 polymorphism of the RANTES gene (p=0.78).

[0025] The remaining predictors were included in the model as statistically significant. The B coefficients were calculated for them, which were used to construct the model equation, as well as the odds ratio values ​​and their 95% confidence intervals (Table 1). Based on the odds ratio estimates for each predictor, it can be concluded that patients with the AA genotype of the rs12411216 polymorphism of the GBA gene and the AA genotype of the rs6265 polymorphism of the BDNF gene have a higher chance of rapid PD progression.

[0026] Table 1. Estimates of predictors of the logistic regression model based on anamnesis data.

[0027] Predictor Coefficient B Predictor significance assessment (p) OSH 95% CI Genotype AArs12411216 GBA_ 4,019 <0,001 55,6 20,6 150,2 Genotype AA rs6265 BDNF 3,667 <0,001 39,1 7,8 195,7 Constant -4,147 <0,001

[0028] Note: Odds ratio (OR) with 95% confidence interval (CI). Predictors were considered significant at p<0.05.

[0029] The logistic regression model equation allows one to calculate the individual probability of rapid progression of PD in a given patient based on molecular genetic characteristics and has the following form:

[0030] P=1 / (1+e -Z ),

[0031] where P is the probability that the event of interest will occur;

[0032] e is a mathematical constant equal to 2.718;

[0033] z is a linear combination of predictors calculated using the formula:

[0034] z = -4.147 + 4.019x1+ 3.667x2

[0035] The values ​​of the predictors in the logistic regression equation are coded as follows: x1=1 in the presence of the AA genotype of the rs12411216 polymorphism of the GBA gene, in the absence of x1=0; x2=1 in the presence of the AA genotype of the rs6265 polymorphism of the BDNF gene, in the absence of x2=0.

[0036] The obtained P value will be between 0 and 1, the cutoff point is selected using ROC analysis, its value is 0.199: if the calculated probability of a rapid PD progression rate is equal to or greater than 0.199, the patient will be assigned to the rapid progression group; if the calculated probability is less than 0.199, the patient will be assigned to the slow progression group.

[0037] The patient classification results obtained using the logistic regression equation were compared with the actual (observed) rates of PD progression in these patients. The model sensitivity was 73.4%, and the specificity was 93.1%. The area under the ROC curve was 0.83 (95% CI 0.79; 0.88), indicating a high quality of the model.

[0038] The proposed solution allows for the assessment of the rate of increase in motor and non-motor symptoms in patients with PD using a safe, relatively inexpensive method – molecular genetic testing.

[0039] The model was constructed using data from 437 observations of patients with PD with a clinically confirmed diagnosis according to the new criteria of the International Parkinson and Movement Disorder Society (MDS) (6). All patients, their relatives, and caregivers included in the study were informed of the nature of the study, its purpose, and potential complications and were free to discontinue the study at any time. All study participants signed voluntary informed consent.

[0040] Each study participant underwent a clinical examination in accordance with official international and Russian guidelines. The study utilized validated questionnaires. Molecular genetic testing was performed on all participants at enrollment.

[0041] Over 5 years of clinical neurological observation in dynamics of 437 patients with PD: it was found that 32 patients had a rapid rate of progression and 405 had a slow rate (combined group).

[0042] For each individual participating in the study, a case report form was completed containing information on demographic data (age, gender, and education level), disease history (duration, stage of symptom development, medication therapy used, presence of dopaminergic agonists, and levodopa equivalent daily dose [LEDD] in PD patients.

[0043] Identifying predictors that indicate the rate of progression of PD is extremely important for the early diagnosis of non-motor symptoms in PD, as well as assessing the effectiveness of treatment, which subsequently has a favorable effect on the prognosis of the disease and improves the quality of life of both patients and their relatives.

[0044] The method is supported by the following clinical examples.

[0045] Clinical example 1. Patient V., male, 58 years old, diagnosed with Parkinson's disease, tremor-like form, stage 2 according to Hoehn and Yahr. The main complaints include general stiffness and resting tremor in the hands, especially in the right.

[0046] Considered himself ill for 4 years, when a resting tremor developed in his right hand. Over the past 6 months, he has noted increasing stiffness and slowness of movement, and about 4 months ago, a resting tremor developed in his left hand.

[0047] Objectively: conscious, oriented in space and time, adequate.

[0048] Cranial nerves – no pathology.

[0049] Moderate hypomimia, oligo- and bradykinesia. Shuffling gait, with small steps. Acheirokinesia, more on the right. Romberg's test is stable. Postural tremor in the right hand. Rapid exhaustion of repeated actions in the right limbs. The face is symmetrical. The pupils are equal, the eye slits are equal. Convergence is weakened. The range of motion in the arms and legs is full, strength is preserved in all muscle groups. Tone: increased, plastic type, more on the right. Reflexes from the arms D = S, moderate briskness. Knee, Achilles reflexes D = S, moderate briskness. There are no pathological wrist or foot signs. Coordination tests are performed. Sensitivity is intact. There are no meningeal signs. Symptoms of tension: negative. A postural instability test was negative. The patient reports having had constipation for about eight years.

[0050] Genotype CA of the rs12411216 polymorphism of the GBA gene, GG of the rs6265 polymorphism of the BDNF gene.

[0051] P=1 / (1+e -Z )

[0052] where P is the probability that the event of interest will occur;

[0053] e is a mathematical constant equal to 2.718;

[0054] z is a linear combination of predictors calculated using the formula:

[0055] z = -4.147 + 4.019x1+ 3.667x2

[0056] The predictor values ​​in the logistic regression equation are coded as follows: x1=0, which corresponds to the absence of the AA genotype of the rs12411216 polymorphism of the GBA gene; x2=0, which corresponds to the absence of the AA genotype of the rs6265 polymorphism of the BDNF gene.

[0057] Z value = -4.147 + 4.019 0+ 3.667 0=-4.147

[0058] P=1 / (1+ e 4,147 )=0.0156

[0059] The resulting value of 0.0156 is less than the cutoff value of 0.199, allowing the patient's PD progression to be classified as slow. The diagnosis made using the model corresponds to the true diagnosis obtained during the patient's 5-year follow-up.

[0060] Case Study 2. Patient K., female, 56 years old, diagnosed with Parkinson's disease, akinetic-rigid form, stage 3 according to Hoehn and Yahr. Main complaints include general stiffness, slowness of movement, and shuffling when walking.

[0061] Considers herself ill for about 4 years, when general stiffness developed. Over the past 3-4 months, she has noted increasing stiffness and slowness of movement.

[0062] Objectively: conscious, oriented in space and time, adequate.

[0063] Cranial nerves – normal. Moderate oligo- and bradykinesia.

[0064] Hypomimia. Shuffling gait, with small steps. Acheirokinesia, more on the right. Stable in the Romberg pose. Mild postural tremor in the hands with a short latency period. Rapid exhaustion of repeated actions in the right limbs. The face is symmetrical. The pupils are equal, the palpebral fissures are equal. Convergence is weakened. The range of motion in the arms and legs is full, strength is preserved in all muscle groups. Tone: increased, plastic type, more on the right. Reflexes from the arms D=S, brisk. Knee and Achilles reflexes are equal, of moderate briskness. There are no pathological wrist or foot signs. The patient performs coordination tests. Sensitivity is intact. There are no meningeal signs. Tension symptoms are negative. According to the patient, constipation and hyposmia have been bothering him for about 9 years.

[0065] Genotype AA of polymorphism rs12411216 of the GBA gene, AA of polymorphism rs6265 of the BDNF gene.

[0066] P=1 / (1+e -Z )

[0067] where P is the probability that the event of interest will occur;

[0068] e is a mathematical constant equal to 2.718;

[0069] z is a linear combination of predictors calculated using the formula:

[0070] z = -4.147 + 4.019x1+ 3.667x2

[0071] The predictor values ​​in the logistic regression equation are coded as follows: x1=1, which corresponds to the AA genotype of the rs12411216 polymorphism of the GBA gene; x2=1, which corresponds to the AA genotype of the rs6265 polymorphism of the BDNF gene.

[0072] Z value = -4.147 + 4.019·1+ 3.667·1=3.538

[0073] P=1 / (1+ e -3,538 )=0.972

[0074] The resulting value of 0.972 is greater than the cutoff value of 0.199, allowing the patient's PD progression to be classified as rapid. The diagnosis made using the model corresponds to the true diagnosis obtained during the patient's 5-year follow-up.

[0075] The claimed method provides the ability to predict the rate of disease progression in patients with a reliable diagnosis of PD according to the new MDS criteria and allows for the use of adequate methods for correcting motor symptoms and preventing / anticipating the development of a wide range of non-motor symptoms that significantly reduce the quality of life of both the patients themselves and their loved ones by correcting so-called modifiable factors that make it possible to clinically “slow down” the functional insufficiency of various neurotransmitter systems of the brain.

[0076] List of references:

[0077] 1. Slominsky PA, Shadrina MI, Alieva AK, Filatova EV, Limborskaya SA. Method for identification of genetic markers of late-onset Parkinson's disease. Russia; RU2663908C1, 2018.

[0078] 2. Seliverstova EV, Seliverstov YuA, Konovalov RN, Krotenkova MV, Illarioshkin SN. A method for diagnosing the neurodegenerative process in Parkinson's disease. Russia; RU2228708C1, 2015.

[0079] 3. Zakharova EYu, Baidakova GV, Pchelina SN, Emelianov AK, Senkevich KA, Nikolaev MA, et al. A method for diagnosing Parkinson's disease associated with mutations in the glucocerebrosidase (gba) gene. Russia; RU2750357, 2022.

[0080] 4. Englev E, Petersen KP. ICH-GCP Guideline: quality assurance of clinical trials. Status and perspectives. Ugeskr Laeger. 14 Apr 2003;16(165):1659–62.

[0081] 5. World Medical Association declaration of Helsinki: Ethical principles for medical research involving human subjects. Vol. 310, JAMA. 2013.

[0082] 6. Skorvanek M, Goldman JG, Jahanshahi M, Marras C, Rektorova I, Schmand B, et al. Global scales for cognitive screening in Parkinson's disease: Critique and recommendations. Vol. 33, Movement Disorders. 2018.